Section Anything

Name: Section Anything
Author: Omniwot

by Omniwotversion 0.1.0i★ –iRuns on your computer

Registry nameio.github.Omniwot/section-anything

Install

Overview

Description from the maker (original English)

A PDF's real sections for agents: heading tree, pages and section text. Free mode is local.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Docs, sheets & office work
You need to fill in: OPENAI_API_KEY, ANTHROPIC_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: OPENAI_API_KEY, ANTHROPIC_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "section-anything": {
      "command": "uvx",
      "args": [
        "section-anything-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "your-value",
        "ANTHROPIC_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add section-anything --env OPENAI_API_KEY=your-value --env ANTHROPIC_API_KEY=your-value -- uvx section-anything-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "section-anything": {
      "command": "uvx",
      "args": [
        "section-anything-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "your-value",
        "ANTHROPIC_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "section-anything": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "section-anything-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "your-value",
        "ANTHROPIC_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

OPENAI_API_KEY secret env
Only for the paid quick and standard modes with OpenAI models
ANTHROPIC_API_KEY secret env
Only for the paid modes with a Claude model

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account Omniwot, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Docs, sheets & office worki

More stars than 0% of the other 2197 servers in this category
Published to the registry more recently than 84% of the other 2197 servers in this category
Basic checks equal to or better than 100% of the other 2197 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Section Anything safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: OPENAI_API_KEY, ANTHROPIC_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 5 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Agent-Native Calendar

by BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

Runs in the cloud★ 7,620MITUpdated 2 months ago

Install

Excel MCP Server

by haris-musa

Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.

Runs on your computer★ 4,276MITUpdated 6 days ago

Install

MCP Server for Excel

by sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

Runs on your computer★ 847MITUpdated 4 days ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Section Anything

Find the real sections of a PDF: every heading, its level, the pages it spans and the exact text under it. Built for RAG pipelines and document tools that need structure, with a dial from free rules to an LLM that reads the whole document, and a hard cost cap on every paid run.

Real output of section-anything 0.1.3, Quick mode (gpt-6-luna), on *Visual Instruction Tuning*, Liu et al., arXiv:2304.08485, CC BY 4.0; the wait for the run is shortened (capture, script). Quick mode's output can vary slightly between runs. Try it on that paper in the Colab notebook (Free mode, no key needed), or in the browser on the Hugging Face Space (Free mode on any PDF, plus saved Quick check and Standard runs on three example papers; don't upload confidential documents).

Pre-release (0.1). The API may change before 1.0.

Website: https://omniwot.github.io/section-anything/ (how it works, benchmarks, examples)

import section_anything

tree = section_anything.section("paper.pdf", mode="quick") print(tree.to_markdown())

# A Study of Sectioning

## 1 Introduction

### 1.1 Scope

## 2 Methods

print(tree.summary()) # mode, model, pages, sections, calls, tokens, cost_usd, seconds

Use from an agent

An agent can take a PDF's outline first and then read only the sections it needs (0.1.6 or newer).

MCP server for Claude Code, Claude Desktop, Cursor and other MCP hosts, with three read-only tools: section_pdf (the heading tree; free mode by default, no model, $0), read_sections (the text of chosen sections) and estimate_cost (what quick and standard would cost).

claude mcp add --transport stdio section-anything -- uvx --from "section-anything[mcp]" section-anything-mcp

Other hosts take the same command in their mcpServers JSON:

{"mcpServers": {"section-anything": {"command": "uvx",

"args": ["--from", "section-anything[mcp]", "section-anything-mcp", "--max-usd", "0"]}}}

Paid modes use the API keys in the server's environment (claude mcp add --env OPENAI_API_KEY=...) and are capped per document by --max-usd (default 0.50; 0 keeps every run free). --root DIR limits the folders the server may read.

Agent skill: copy skills/section-anything into your agent's skills folder (Claude Code: ~/.claude/skills/) and the agent uses the command line the same way: outline, then the sections it needs.

Shell: section-anything paper.pdf --format json --body prints every section with its heading_path, parent, pages and text.

Why

PDF converters mostly infer headings from how a line looks, so paper titles, author names, captions and theorem statements can come out as sections, and real subsections can get the wrong level. Anything that chunks or navigates by headings inherits those mistakes. Section Anything combines the PDF's own outline (bookmarks) and printed table of contents, typography and numbering rules, and optionally a model that reviews or reads the text.

Results

Heading-tree similarity (TEDS, 0–100, higher is better) on READoc with READoc's own scoring code, October 2026. Docling and MinerU convert whole documents (layout, tables, figures, formulas, OCR); these numbers compare only the heading tree. Papers not used while developing the method:

READoc arXiv papers (held out)	Docs	TEDS
Section Anything `standard` (gpt-6-luna)	905	70.0
Section Anything `quick` (gpt-6-luna)	905	68.0
Section Anything `free` (no model)	905	60.0
Docling 2.140 (heading hierarchy on)	905	49.4

quick is release 0.1.2 and free release 0.1.5. 0.1.1 found the abstract's heading (journals often set it small, bold or run into the first line): +2.4 to free and +3.7 to quick in a pre-registered held-out test (0.1.0: 54.8 and 63.9). 0.1.2 keeps a section number that the PDF extractor split off its title ("1" | "Introduction"): +0.7 to free (95% CI +0.5 to +1.0) and +0.5 to quick (95% CI +0.4 to +0.8; +1.7 on the 291 papers it changes) in a second pre-registered test (0.1.1: 57.2 and 67.4). 0.1.5 gives back matter (References, Acknowledgements, Appendix) and appendix sections the level of the numbered sections: +2.1 to free (95% CI +1.7 to +2.4; 136 papers better, 4 worse) in a fourth pre-registered test on these papers (0.1.4: 57.9); READMEs unchanged. standard uses none of these. See the changelog.

On the same 905 papers with MinerU's cloud (3.4.4, VLM): our standard 70.0, our quick 68.0, MinerU + its own LLM title levels (gpt-6.1-sol) 64.8 (paired difference: standard +5.1, 95% CI +4.0 to +6.2, or +2.8 without the 154 papers where that step, run by us on gpt-6.1-sol, returned no parsable levels and kept MinerU's raw levels; quick +3.1, 95% CI +2.1 to +4.1, but level without those papers: +1.0, 95% CI −0.03 to +2.0), MinerU alone 53.9, Docling 49.4.

On GitHub READMEs, free scores higher than Docling: on 1,112 bookmarked READoc READMEs not used in development, 81.9 against 75.5, and Docling reaches 79.7 with the opt-in outline check we proposed upstream (docling#5002), the same idea as free's outline check. On 27 UK government reports never used in development (answer keys from each report's HTML version), the outline check improved free by +5.7 (95% CI +0.4 to +12.2; 43.1 → 48.8; measured on 0.1.0).

Where others win: on the 1,124 held-out READoc READMEs our quick and standard only tie with Docling (about 75). On the 905 held-out papers Docling scored higher than standard on 103 papers and lower on 773 (by more than 0.5 points). Nougat, an OCR model trained on arXiv, has the highest published READoc arXiv score (88.5 in the READoc paper, older tool versions; we have not run it). Docling and MinerU also read scanned pages with OCR; Section Anything needs a text layer. Better headings improved RAG retrieval in our Qasper test but not answer quality.

Settings and cost

Mode	What runs	Sent to a model	Cost per 1,000 pages
`free` (default)	bookmarks or the printed contents as the outline, then typography and numbering rules; headings a complete-looking outline does not list are dropped	nothing	$0
`quick`	rules propose candidate heading lines; a small model keeps the real ones and sets levels	candidate lines only	about $0.07 (gpt-6-luna)
`standard`	a model reads every line, with font hints, and marks where sections start and end	the document text	about $0.16 (gpt-6-luna, the default); $2.90 with gpt-6.1-sol
`local:`	`quick`, answered by a local Ollama model	nothing leaves the machine	$0

Every paid run is estimated first and capped (default $0.50 per document); over the cap it downgrades (standard → quick → free) or fails, as you choose.

The default model for quick and standard is gpt-6-luna, the model behind their READoc scores above. standard can run on gpt-6.1-sol instead (SECTIONANY_STANDARD_MODEL=gpt-6.1-sol or model="gpt-6.1-sol") at about 18 times the cost. On development documents only (98 READoc papers and 100 READMEs, same code) it scored 5.8 points higher on READMEs (95% CI +2.1 to +9.6) and 0.9 higher on papers (CI -0.3 to +2.1, not significant); this is not confirmed on held-out documents.

Install

Python 3.11 or newer:

pip install section-anything

pip install "section-anything[anthropic]" # optional: Claude models on Anthropic's own API pip install "section-anything[docling]" # optional: tree.to_docling_document() pip install "section-anything[langfuse]" # optional Langfuse tracing pip install "section-anything[mcp]" # optional MCP server: section-anything-mcp

latest from GitHub:

pip install "git+https://github.com/Omniwot/section-anything#subdirectory=packages/section-anything"

Command line:

section-anything paper.pdf                                # free, Markdown headings

section-anything paper.pdf --mode quick --format json # JSON with spans and cost section-anything paper.pdf --mode standard --max-usd 0.5 # cap this document at $0.50

API keys come from the environment only (SECTIONANY_API_KEY, or OPENAI_API_KEY for OpenAI's endpoint); any OpenAI-compatible endpoint works. Claude models run on Anthropic's own API with the anthropic extra and ANTHROPIC_API_KEY; on development documents Claude Haiku 5.5 tied the default at about 3 times the cost (Providers). Full options, output format and the security model for untrusted PDFs: packages/section-anything/README.md.

Integrations

One document per section, with the heading path, pages and character span as metadata. Each package depends only on section-anything and the framework's core package.

pip install langchain-section-anything

pip install llama-index-readers-section-anything pip install lightrag-section-anything

Framework	Package	Use
LangChain	`langchain-section-anything`	`SectionAnythingLoader("paper.pdf", mode="free").load()`
LlamaIndex	`llama-index-readers-section-anything`	`SectionAnythingReader(mode="free").load_data("paper.pdf")`, or as the `.pdf` reader of `SimpleDirectoryReader`
LightRAG	`lightrag-section-anything`	parser engines (`sectionany_free`, `sectionany_quick`, ...) for LightRAG's heading-based chunker, without a MinerU or Docling service

To run Docling's HybridChunker or Unstructured's chunk_by_title on these headings, export the tree with tree.to_docling_document() or tree.to_unstructured_elements() (how).

Limitations

Reads the PDF's text layer; scanned PDFs need OCR first.
Tables, figures and equations are not structured; their text stays in the section text.
free is best when the PDF has bookmarks or a printed table of contents. When the bookmarks look complete, it drops headings they do not list; if the bookmarks stop at the top levels, real deeper headings are lost (about 6% of READMEs lose more than 5 points). Turn this off with SECTIONANY_DEMOTE_UNLISTED_HEADINGS='[]'.
quick and standard send text to the provider you configure.

Repository

Path	What it is

| packages/section-anything/ | the library and CLI (Apache-2.0)

Only the beginning is shown; read the rest in the repo

Section Anything

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Docs, sheets & office worki

Common questions

Alternatives

Agent-Native Calendar

Excel MCP Server

MCP Server for Excel

README from the maker

Section Anything

# A Study of Sectioning

## 1 Introduction

### 1.1 Scope

## 2 Methods

Use from an agent

Why

Results

Settings and cost

Install

latest from GitHub:

Integrations

Limitations

Repository